I have 4 sites with a total of 22 species (i.e. site1 has 7 species, site 2 has 15, etc.). I also have multiple weeks’ species abundance data for each site. I want to analyze the species diversity on temporal and spatial scale based on high throughput sequencing.
Several methods have been proposed to compare sites for the species richness, many of which only use presence/absence data. I want to use abundance data, and do the following:
-use entire dataset, compare the similarity statistically, and obtain an optimum species richness/diversity value (say x number of species needed to reach 95% coverage of the whole dataset)
-use subsampled dataset (time-wise and site-wise), and analyze at which stage the previously obtained optimum number of species is reached (i.e., at 2 months of sampling instead of 12 or in one site instead of 4, etc.)
Any recommendations on the use of abundance data for answering these questions?
Trend-surface analysis can be the best way to express spacial distribution of variables.
Hello Bilgenur,
I hope you are well. Please, check this paper:
https://www.researchgate.net/publication/6869079_Abundance-Based_Similarity_Indices_and_Their_Estimation_When_There_Are_Unseen_Species_in_Samples
Cheers!
N
Article Abundance-Based Similarity Indices and Their Estimation When...
Hi Bilengenour,
if If you are familiar with the R language I suggest to use a glm for count data (poissono or quasipoisson). See the attached guides.
All the best,
Dan.
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